Title: Intelligent condition perception network towards sustainable manufacturing capability for manufacturing systems

Authors: Quan Liu; Aiming Liu; Yuanming Li; Wenjun Xu; Jiayi Liu; Gaobo Chen; Wei Dai

Addresses: School of Information Engineering, Wuhan University of Technology, Wuhan, China; Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, Wuhan 430070, China ' School of Information Engineering, Wuhan University of Technology, Wuhan, China; CBMI Construction Co., Ltd., 7 Longqing Street, Beijing 100176, China ' School of Information Engineering, Wuhan University of Technology, Wuhan, China; Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, Wuhan 430070, China ' School of Information Engineering, Wuhan University of Technology, Wuhan, China; Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, Wuhan 430070, China ' School of Information Engineering, Wuhan University of Technology, Wuhan, China; Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, Wuhan 430070, China ' School of Information Engineering, Wuhan University of Technology, Wuhan, China; Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, Wuhan 430070, China ' School of Information Engineering, Wuhan University of Technology, Wuhan, China; Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, Wuhan 430070, China

Abstract: Sustainability has become an important factor from which we can judge the performance of modern manufacturing systems. The condition perception of sustainable manufacturing capability (SMC) can provide reliable manufacturing information and data support for manufacturing systems. This paper proposes an intelligent condition perception network (ICPN) for SMC of manufacturing systems, which focuses on the production condition monitoring, the energy consumption metering, and the perception data transfer. The proposed hybrid wireless perception network consists of the embedded Radio Frequency Identification (RFID) perception modules, embedded energy consumption perception modules and environment perception modules. In view of the several heterogeneous networks might coexist in the manufacturing environment, the heterogeneous networks adaptation device is designed to figure out the problem of differences of data transmission in heterogeneous networks. Finally, a prototype system is deployed in a laboratory environment. The experimental results demonstrate that the system can satisfy the requirements of condition perception for SMC.

Keywords: intelligent condition perception network; ICPN; sustainable manufacturing capability; SMC; manufacturing systems; production process; energy consumption; heterogeneous network adaptation.

DOI: 10.1504/IJMR.2017.086172

International Journal of Manufacturing Research, 2017 Vol.12 No.3, pp.287 - 304

Received: 28 Apr 2016
Accepted: 16 Aug 2016
Published online: 28 Aug 2017 *

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